Transporters catalyze entry and exit of molecules into and out of cells and organelles. They achieve cellular homeostasis, are responsible for multidrug resistance in pathogens and tumors, and when defective, cause dozens of important human genetic diseases. Our laboratory maintains, updates and improves the Transporter Classification Database, TCDB, which houses the Transporter Classification (TC) system, adopted officially by the International Union of Biochemistry and Molecular Biology (IUBMB). TCDB is the internationally acclaimed, carefully annotated, universal standard for classifying and providing information about transporters and transport-related proteins in all major domains of life. It presents sequence, biochemical, physiological, pathological, structural and evolutionar data about these proteins and the transport systems they comprise. It uses a successful system of classification based on transporter class, subclass, family, subfamily, individual transport systems and constituent proteins. In this competitive renewal of GM0077402, we propose to expand, update, automate and interlink TCDB. In particular, we will collaborate to integrate and unify the classification systems used by TCDB and Pfam with the formation of a TC ontological system. We will generate new data concerning transport proteins, and expand procedures for making functional predictions. This last effort will derive reliable new biological knowledge from a variety of sources, including phylogeny, motif, domain, operon and regulon analyses. Our Specific Aims are as follows: 1. To compare and evaluate methods of homology establishment, e.g., our and Pfam's statistical approaches, as well as introduce a system of protein repeat unit and domain identification. We will confirm and extend homology results based on structural superimpositions and profile: profile comparisons. We will develop and implement pipelines for the exchange of information between Pfam and TCDB and standardize both classification systems. 2. To incorporate our family descriptions into Wikipedia, to facilitate community annotation and interaction. Thus, we will add to Wikipedia, and integrate with Pfam to create a common platform for community annotation. 3. To create a substrate ontological framework for TCDB, using ChEBI and GO. 4. To use and automate multiple approaches, including phylogeny and synteny, to derive reliable functional predictions and provide guides for other researchers to do the same. 5. To utilize our TCDB advisory board for continued knowledgebase modernization and sustainability.